Entities, such as financial institutions, may utilize a large number of statistical models in the performance of business operations. The statistical models may be utilized as tools in decision-making processes, and the business operations may include, for instance, granting of loans, marketing, opening of accounts, extending credit, processing of payments, soliciting new customers, and the like. The statistical models may be used in the performance of those business operations to guide business analysis and provide indications of probabilities of success of the operations, in light of various relevant financial, individual, and environmental variables.
Such statistical models may be extremely complex and may include a plurality of mathematical equations and/or relationships, each associated with a plurality of variables. Further, development of such statistical models may require coordination of effort and communication amongst a large number of individuals (collaborators). The collaborators may be located in disparate geographical regions, and each collaborator may have distinct duties that require simultaneous transmission of data from other collaborators. Additionally, development and implementation of the statistical models may require the generation, distribution, and management of large quantities of printed and electronic documentation.
Conventional methods for statistical model development and management therefore require collection, organization, and transmission of a large quantity of independent pieces of paper and electronic documentation, as well as complicated management of schedules and communication of collaborators. Collaborators may need to be appraised of schedules and statuses of other collaborators, and each collaborator may need to be alerted of statuses of required tasks. The statistical model development procedures may require that the collaborators manually coordinate development schedules, relay status information, transport documentation, and alert other collaborators regarding necessity of additional activity. Each of the above tasks may be required to be performed several times for each of a large number of collaborators. Such a required level of complexity and manual information management and transmission is extremely cumbersome, inefficient, prone to errors, and may introduce opportunities for loss of documentation, experimental data, and other important information.
Accordingly, a need exists for methods and systems for managing such schedules, documentation, data, alerts, and other information associated with development and implementation of models.